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<strong>WhiteICE information</strong> |
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Idea of the software is that you run the sound stimulation in background while using a computer. Stimulation requires many hours of measurements before it is effective. Sounds used are very simple because the learning starts from scratch (TODO: collect database of measurements and models that can be used without long training + generate music instead of plain sounds). |
Idea of the software is that you run the sound stimulation in background while using a computer. Stimulation requires many hours of measurements before it is effective. Sounds used are very simple because the learning starts from scratch (TODO: collect a database of measurements and models that can be used without a long training time + generate music instead of plain sounds). |
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Command-line version of WhiteICE has more options. You start listening a LSL stream from EEG in a local network by using a command: |
Command-line version of WhiteICE has more options. You start listening a LSL stream from EEG in a local network by using a command: |
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Or for increasing intelligence (should have 8 channel EEG for good results, maximizing certain approximate small world index value): |
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| ⚫ | The command plays sounds in the background (while using a computer), tries to increase concentration and uses first 4 channels found from the first LSL stream found from the network. If you are using "BrainAccess MINI EEG" for example which has 8 channels, you use command "--lsl-channels=8". The default number of LSL channels is 4. |
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<code> |
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whiteice --measure --device=lsl --intelligence --lsl-channels=8 |
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</code> |
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| ⚫ | The command plays sounds in the background (while using a computer), tries to increase concentration and uses first 4 channels found from the first LSL stream found from the network. If you are using "BrainAccess MINI EEG" for example which has 8 channels, you use command "--lsl-channels=8". The default number of LSL channels is 4. LSL stream listened is currently either "EEG", "Eeg" or "eeg" but this will be become configurable later. |
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In practice you need to run software for hours to get small average positive effect to target values. |
In practice you need to run software for hours to get small average positive effect to target values. |
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Also read: [[WhiteICE version information]] |
Also read: [[WhiteICE version information]], [[Measurements]] |
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<strong>Hosaka information</strong> |
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Hosaka is currently not actively developed because it does off-line optimization of larger machine learning model (you must first measure responses for hours, then compute model for hours and finally can use non-adapting model with real data). However, currently Hosaka supports using of different pictures as stimulations which feature vectors will be computed for machine learning prediction of responses to pictures. |
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Latest revision as of 18:51, 6 September 2026
WhiteICE information
Idea of the software is that you run the sound stimulation in background while using a computer. Stimulation requires many hours of measurements before it is effective. Sounds used are very simple because the learning starts from scratch (TODO: collect a database of measurements and models that can be used without a long training time + generate music instead of plain sounds).
Command-line version of WhiteICE has more options. You start listening a LSL stream from EEG in a local network by using a command:
whiteice --measure --device=lsl --concentration --lsl-channels=4
Or for increasing intelligence (should have 8 channel EEG for good results, maximizing certain approximate small world index value):
whiteice --measure --device=lsl --intelligence --lsl-channels=8
The command plays sounds in the background (while using a computer), tries to increase concentration and uses first 4 channels found from the first LSL stream found from the network. If you are using "BrainAccess MINI EEG" for example which has 8 channels, you use command "--lsl-channels=8". The default number of LSL channels is 4. LSL stream listened is currently either "EEG", "Eeg" or "eeg" but this will be become configurable later.
In practice you need to run software for hours to get small average positive effect to target values.
If you have Interaxon Muse instead, you must configure MindMonitor app to send OSC stream to your computers IP and port 4545 and use a command (the number of channels is always 4):
whiteice --measure --device=mindmonitor --concentration
Also read: WhiteICE version information, Measurements
Hosaka information
Hosaka is currently not actively developed because it does off-line optimization of larger machine learning model (you must first measure responses for hours, then compute model for hours and finally can use non-adapting model with real data). However, currently Hosaka supports using of different pictures as stimulations which feature vectors will be computed for machine learning prediction of responses to pictures.